Independence is a central concern for people in the care of many chronic conditions. It is often viewed as a goal that can be facilitated with the use of patient data. It is also viewed, especially from the medical side, as something an individual achieves. However, in the lived experience, independence is often a set of collaborative practices. In this paper, we unpack findings from an interview-based study of Spinal Cord Injury (SCI) self-care. We found that independence - both functional and in the form of effecting agency - must be co-constructed by the choices and activities of the care network, including the person with disability, caregivers, and clinicians. This collaboratively shaped independence also affects potential collection and use of data in support of self-care. We describe how collaboratively shaped independence informs requirements and constraints for the design of sensor-based networks for self-care in long-term chronic disability.

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Lung cancer screening, a relatively new procedure, is widely considered to be a promising way to address the low chances of survival from this disease by catching it at an earlier, more treatable stage. However, deciding whether to get this screening can be complicated for an individual; as such, patient decision aids are used to facilitate this process. To co-design a lung cancer decision aid, we conducted 5 participatory design workshops with 17 participants from African American and Latinx populations from communities with low resources. We also conducted 5 focus groups with 21 African-American participants to provide evaluative feedback. Through triangulating our fieldwork findings with other stakeholders, we detail the challenges of designing an inclusive decision aid and offer some suggestions with concrete examples, which complement current content-based guidelines, to assist in other patient decision aid development. We then discuss implications for applications to support decision-making in pervasive environments. CCS CONCEPTS• Human-centered computing → User centered design; Webbased interaction; • Applied computing → Life and medical sciences; Health informatics. KEYWORDSparticipatory design, patient decision support, cancer screening ACM Reference Format: